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Adaptive traffic control systems need to continuously monitor traffic conditions and predict immediate traffic conditions to respond to changes in both recurrent and nonrecurrent traffic patterns. One measure of traffic conditions is the number of turning vehicles at intersections and freeway offramps. Split parameters may be estimated from the numbers of turning vehicles, and along with upstream traffic counts, these may be used to predict the numbers of downstream vehicle arrivals. This study develops several responsive methods to estimate split parameters for four-legged intersections and freeway segments from vehicle counts. For intersections, these methods depend on the geometric layout of the intersection and the signal stage. The vehicle counts are collected by signal stages and lanes. The split parameters or turning proportions are estimated for each signal stage and, then they are combined to estimate the turning proportions for the entire interval. Some methods need counts for only one cycle to estimate turning proportions while others need additional data. For those methods that need additional data, four closed-form estimation methods are developed. Two methods need prior turning proportion estimates: (1) maximum entropy (ME) and (2) generalized least-squared error (GLS). The other methods require counts for three cycles: (3) least-squared error (LS) and (4) least-squared error/generalized least-squared error (LS/GLS). Results from these methods are compared with each other. The ME, GLS and LS methods which use cycle counts are also developed and their results are compared with the results of their stage-count counterparts. For freeway segments, a virtual box method for consistent vehicle counting is developed. Three split parameter estimation methods are developed for freeway segments. One method, GLS, uses counts, from one virtual box and requires prior split parameter estimates. The other methods, LS and GLS/LS, need several virtual boxes, depending on the number of interchanges in the freeway segment. Split parameter estimation approaches are also developed for small road networks by combining split parameters from individual intersections and freeway segments.

In order to deal with the competitive environment surrounding the air transport industry, civil aviation authorities have undertaken several approaches to improve airport efficiency, such as investing in the infrastructure and privatising airport ownership or governance. Among these methods, airport privatisation policy has been implemented for around 25 years in the U.K., closely followed by other European countries. By contrast, decision makers elsewhere, such as in the Asia-Pacific region, are now interested in privatisation and in doing so evaluate the impact of this process elsewhere. Focussing on the most popular method for assessing airport efficiency, with Data Envelopment Analysis (DEA) a unit can appear efficient simply because of its pattern of inputs and outputs rather than any inherent efficiency. But only using DEA may not provide useful results about the efficiency of airports as different decision makers may weight the relative importance of inputs and outputs differently (for example, airport managers, and airline companies). In this research, another aim is to develop and demonstrate the applicability of different analysis techniques within the AEES. For this reason, Analytic Hierarchy Process (AHP) analysis is adopted to calculate the importance of each variable. These results are then integrated into both DEA and DEA, Assurance Region (AR) models, to reflect the different importance of the metrics. In the context of air transportation, an integrated AHP/DEA and AHP/DEA-AR model are applied for the first time to evaluate airport efficiency. A sensitivity analysis with different variable sets is carried out. In conclusion, an AEES is established and the result shows that the approach by adopting AHP/DEA-AR model in particular can provide more accurate values of relative efficiency than using the traditional DEA approach. There are also different priorities between stakeholder groups and these can affect the efficiency scores of airports. However, the results for each of the different analysis techniques show that there is no statistically significant relationship between airport ownership and efficiency. Therefore, the primary aim of this research is to examine the relationship between airport privatisation and efficiency, through an Airport Efficiency Evaluation System (AEES). The study covers Europe and the Asia-Pacific region, reflecting different attitudes towards the role of government within airport management. Focussing on the most popular method for assessing airport efficiency, with

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This thesis studies the benefits and costs of urban living. Chapter 1 is a theoretical and empirical analysis of the benefits of urban density for consumers, while Chapter 2 proposes a model of how cities enhance the incentives for knowledge diffusion. Chapter 3 investigates the costs of congestion and the determinants of car travel speed across US cities. In Chapter 1, I study the consumption value of urban density by combining Google’s local business data with microgeographic travel data. I show that increased density enables consumers to both realize welfare gains from variety and save time through shorter trips. I estimate the gains from density in the restaurant industry, identifying willingness to pay for access to a slightly preferred location from the extra travel costs incurred to reach it. The results reveal large but very localized gains from density. Increasing the density of destinations generates little reduction in trip times, so most of these gains from density are gains from variety, not savings on travel time. In Chapter 2, I propose a new micro-foundation for knowledge spillovers. I model a city in which uncompensated knowledge transfers to entrepreneurs are bids by experts in auctions for jobs. The model derives from the key ideas about how knowledge differs from other inputs of production, namely that knowledge must be possessed for its value to be assessed, and that knowledge is freely reproducible. Agglomeration economies result from growth in the number of meetings between experts and entrepreneurs, and from heightened competition for jobs among experts. In Chapter 3, written jointly with Gilles Duranton and Matt Turner, we investigate the determinants of driving speed in large US cities. We first estimate city level supply functions for travel in an econometric framework where both the supply and demand for travel are explicit. These estimations allow us to calculate a city level index of driving speed. Our investigation of the determinants of speed provides the foundations for a welfare analysis. This analysis suggests large gains in speed if slow cities can emulate fast cities, and sizable deadweight losses from congestion.

This thesis studies the benefits and costs of urban living. Chapter 1 is a theoretical and empirical analysis of the benefits of urban density for consumers, while Chapter 2 proposes a model of how cities enhance the incentives for knowledge diffusion. Chapter 3 investigates the costs of congestion and the determinants of car travel speed across US cities. In Chapter 1, I study the consumption value of urban density by combining Google’s local business data with microgeographic travel data. I show that increased density enables consumers to both realize welfare gains from variety and save time through shorter trips. I estimate the gains from density in the restaurant industry, identifying willingness to pay for access to a slightly preferred location from the extra travel costs incurred to reach it. The results reveal large but very localized gains from density. Increasing the density of destinations generates little reduction in trip times, so most of these gains from density are gains from variety, not savings on travel time. In Chapter 2, I propose a new micro-foundation for knowledge spillovers. I model a city in which uncompensated knowledge transfers to entrepreneurs are bids by experts in auctions for jobs. The model derives from the key ideas about how knowledge differs from other inputs of production, namely that knowledge must be possessed for its value to be assessed, and that knowledge is freely reproducible. Agglomeration economies result from growth in the number of meetings between experts and entrepreneurs, and from heightened competition for jobs among experts. In Chapter 3, written jointly with Gilles Duranton and Matt Turner, we investigate the determinants of driving speed in large US cities. We first estimate city level supply functions for travel in an econometric framework where both the supply and demand for travel are explicit. These estimations allow us to calculate a city level index of driving speed. Our investigation of the determinants of speed provides the foundations for a welfare analysis. This analysis suggests large gains in speed if slow cities can emulate fast cities, and sizable deadweight losses from congestion.

Collaborative consumption is the culture of sharing instead of ownership in consumer behaviours. Transportation services such as ridesharing, carsharing, and bikesharing have recently adopted collaborative business models. Such services require real-time management of the available fleets to increase revenues and reduce costs. This thesis proposes two dynamic models for real-time management of carsharing and ridesharing services. In ridesharing, an assignment problem is solved to match drivers with passengers. The model is expanded to include multi-passenger and multi-driver matches. In carsharing, vehicles are relocated between parking stations to service the users. Results of the two models are compared to benchmark models which provide lower-bound solutions.

Collaborative consumption is the culture of sharing instead of ownership in consumer behaviours. Transportation services such as ridesharing, carsharing, and bikesharing have recently adopted collaborative business models. Such services require real-time management of the available fleets to increase revenues and reduce costs. This thesis proposes two dynamic models for real-time management of carsharing and ridesharing services. In ridesharing, an assignment problem is solved to match drivers with passengers. The model is expanded to include multi-passenger and multi-driver matches. In carsharing, vehicles are relocated between parking stations to service the users. Results of the two models are compared to benchmark models which provide lower-bound solutions.

<p> Shipping, the ocean transportation of people and goods, moves most world trade, and understanding its effects is required to assess human use of the oceans. This work examines the shipping trade by combining global observations of ship location with vessel identification records, and interpreting the results in an ecological context. By incorporating quality checking methods with volunteered geographic information, I provide a spatially resolved high resolution dataset which links individual ships with their movement patterns and vessel attributes. This contributes knowledge on the state and distribution of shipping, and identifies areas where mitigation of impacts are achievable. </p>

<p> I begin this dissertation with a historical overview of the demographic, economic, and political trends that have helped shape existing urban form, transportation infrastructure, and travel behavior in Mexico City. Despite an uptick in car ownership and use, most households&mdash;both urban and suburban&mdash;continue to rely on public transportation. Furthermore, suburban Mexico City has lower rates of car ownership and use than its central areas. In subsequent chapters, I frame, pose, and investigate three interrelated questions about Mexico City's evolving suburban landscape, the nature of households' travel decisions, and the relationship between the built environment and travel behavior. Together, these inquiries tell a story that differs significantly from narratives about US suburbs, and provide insight into the future transportation needs and likely effects of land and transportation policy in these communities and others like them in Mexico and throughout the developing world.</p><p> First, how has the influence of the built environment on travel behavior changed as more households have moved into the suburbs and aggregate car use has increased? Using two large metropolitan household travel surveys from 1994 and 2007, I model two related-but-distinct household travel decisions: whether to drive on an average weekday, and if so, how far to drive. After controlling for income and other household attributes, I find that the influence of population and job density on whether a household undertakes any daily car trips is strong and has increased marginally over time. By contrast, high job and population densities have a much smaller influence on the total distance of weekday car travel that a household generates. For the subset of households whose members drive on a given weekday, job and population densities have no statistical effect at all. Contrary to expectations, a household's distance from the urban center is strongly correlated with a lower probability of driving, even after controlling for income. This effect, however, appears to be diminishing over time, and when members of a household drive, they drive significantly more if they live farther from the urban center. The combination of informal transit, public buses, and the Metro has provided sufficient transit service to constrain car use in the densely populated suburban environments of Mexico City. Once suburban residents drive, however, they tend to drive a lot regardless of transit or the features of the built environment.</p><p> Second, how much are the recent trends of increased suburbanization, rising car-ownership, and the proliferation of massive commercially-built peripheral housing developments interrelated? To investigate this question, I first disentangle urban growth and car ownership trends by geographic area. The fastest-growing areas tend to be poorer and have had a much smaller impact on the size of the metropolitan car fleet than wealthier, more established neighborhoods in the center and western half of the metropolis. I then zoom in to examine several recent commercial housing developments. These developments, supported by publicly-subsidized mortgages, contain thousands of densely-packed, small, and modestly-priced housing units. Their residents remain highly reliant on public transportation, particularly informal transit, and the neighborhoods become less homogenous over time as homeowners convert units and parking spaces to shops and offices. Finally, I use the 2007 household travel survey to model households' intertwined decisions of where to live and whether to own a car. If housing policy and production cannot adapt to provide more centrally-located housing, growing incomes will tend to increase car ownership but concentrate more of it in areas where car-owning households drive much farther.</p><p> Third, how has the Metro's Line B, one of the first and only suburban high-capacity transit investments, influenced local and regional travel behavior and land use? To explore this question, I compare travel behavior and land use measures at six geographic scales, including the investment's immediate catchment area, across two time periods: six years before and seven years after the investment opened. Line B, which opened in stages in 1999 and 2000, significantly expanded Metro coverage into the densely populated and fast-growing suburban municipality of Ecatepec. While the investment sparked a significant increase in local Metro use, most of this increase came from people relying on informal transit, rather than cars. While this shift reduced transit fares and increased transit speeds for local residents, it also increased government subsidies for the Metro and had no apparent effect on road speeds. Furthermore, the Metro remains highly dependent on informal transit to provide feeder service even within Ecatepec. In terms of land use, the investment increased density around the stations but appears to have had little to no effect on downtown commercial development. In short, the effects of Line B demonstrate much of the promise and problem with expanding high capacity transit service into the suburbs. (Abstract shortened by UMI.)</p>